Tusimple, Inc.

Beijing Tusen Zhitu Technology Co., Ltd.

Zehua Huang

Xiaoling Han

Charles A Price

Panqu Wang

Pengfei Chen

Kaixin Zheng

Kun Zhang

Xiaodi Hou

Siyuan Liu

Lingting Ge

Todd B Skinner

Ke Xu

Yu-Ju Hsu

Xue Mei

Chenzhe Qian

Ruiliang Zhang

Zhujia Shi

Yixin Yang

Yue Pan

Frederic Rocha

Yijie Wang

Mohamed Hassan Ahmed Hassan Wahba

Esayas Naizghi

Shuhan Yang

Junjun Xin

Wei Liu

Lei Su

Lei Nie

Dinghua Li

Changyi Zhao

Jiangming Jin

Yifan Gong

Qiong Xu

Yicai Jiang

Zhaohan Jia

Zhiqi Gong

Yu Zhang

Zijie Xuan

Arda Kurt

Zhipeng Yan

Yishi Liu

Tian Li

Jeffrey J Renn

Yujia Wu

Pingyuan Ji

Jade E Day

Xiangchen Zhao

Jay Day

Weina Mao

Yijing Li

Joshua Miguel Rodriguez

Chiyu Zhang

Jianqiu Cao

Xialing Han

A redundant hardware and software architecture can be designed to enable vehicles to be operated in an autonomous mode while improving the reliability and/or safety of such vehicles. A system for redundant architecture can include a set of at least two redundant sensors coupled to a vehicle and configured to provide timestamped sensor data to each of a plurality of computing unit (CU) computers. The CU computers can process the sensor data simultaneously based on at least a time value indicative of an absolute time or a relative time and based on the timestamped sensor data. The CU computers provide to a vehicle control unit (VCU) computer at least two sets of outputs configured to instruct a plurality of devices in a vehicle and cause the vehicle to be driven.

Redundant hardware and software architecture for autonomous vehicles

A system installed in a vehicle includes a first group of sensing devices configured to allow a first level of autonomous operation of the vehicle; a second group of sensing devices configured to allow a second level of autonomous operation of the vehicle, the second group of sensing devices including primary sensing devices and backup sensing devices; a third group of sensing devices configured to allow the vehicle to perform a safe stop maneuver; and a control element communicatively coupled to the first group of sensing devices, the second group of sensing devices, and the third group of sensing devices. The control element is configured to: receive data from at least one of the first group, the second group, or the third group of sensing devices, and provide a control signal to a sensing device based on categorization information indicating a group to which the sensing device belongs.

Sensor layout techniques

A power management system is disclosed for managing power in a vehicle. The system may include a power distribution unit (PDU) communicably coupled to a power controller unit located in the vehicle. The power controller unit comprises a microcontroller configured to: receive, from the PDU, a temperature value that indicates a temperature of the PDU, one or more voltage values from the one or more voltage sensors, or one or more current values from the one or more current sensors, perform a determination that the temperature value, the one or more voltage values, or the one or more current values are below one or more of their respective pre-determined threshold values, and send, after the determination, a health status message to a computer located in the vehicle, where the health status message indicates that the PDU is operating in a safe operating condition.

Power management system for autonomous vehicles

Disclosed are devices, systems and methods for capturing an image. In one aspect an electronic camera apparatus includes an image sensor with a plurality of pixel regions. The apparatus further includes an exposure controller. The exposure controller determines, for each of the plurality of pixel regions, a corresponding exposure duration and a corresponding exposure start time. Each pixel region begins to integrate incident light starting at the corresponding exposure start time and continues to integrate light for the corresponding exposure duration. In some example embodiments, at least two of the corresponding exposure durations or at least two of the corresponding exposure start times are different in the image.

Adaptive illumination for a time-of-flight camera on a vehicle

Described are devices, systems and methods for managing power generation, storage and/or distribution in autonomous vehicles. In some aspects, a system for power management in an autonomous vehicle having a main power source and one or more alternators includes a vehicle control unit, a secondary power source, and a power management unit. In some embodiments, the power management unit is configured on an autonomous vehicle having a single alternator-charging system for battery charging and battery power control with different battery packs. In some embodiments, the power management unit is configured on an autonomous vehicle having multiple alternator-charging systems for battery charging and battery power control for different battery packs.

Battery power control in autonomous vehicles having alternator-charging systems

Described are devices, systems and methods for managing a supplemental brake control system in autonomous vehicles. In some aspects, a supplemental brake management system includes brake control hardware and software that operates with a sensing mechanism for determining the brake operational status and a control mechanism for activating the supplemental brake control in an autonomous vehicle, which can be implemented in addition to the vehicle's primary brake control system.

Supplemental braking control system in autonomous vehicles

Disclosed are distributed computing systems and methods for controlling multiple autonomous control modules and subsystems in an autonomous vehicle. In some aspects of the disclosed technology, a computing architecture for an autonomous vehicle includes distributing the complexity of autonomous vehicle operation, thereby avoiding the use of a single high-performance computing system and enabling off-the-shelf components to be use more readily and reducing system failure rates.

Distributed computing systems for autonomous vehicle operations

Techniques are described for transitioning control of a steering system from an autonomous mode in a vehicle to a driver-controlled mode where the driver can control the steering wheel of the steering system. A method includes receiving values that describe an amount of torque and a direction of torque in response to a torque applied to a steering wheel of a steering system operated in an autonomous mode, determining that the values are either greater than or equal to a threshold value or are less than or equal to a negative of the threshold value, determining that the values are measured over a period of time greater than or equal to a pre-determined amount of time, and transitioning the steering system from being operated in the autonomous mode to being operated in a driver-controlled mode in which the steering system is under manual control.

Transitioning steering control from an autonomous vehicle to a driver

Techniques are described for managing temperature in an autonomous vehicle. An exemplary method comprises performing autonomous driving operations that operate the autonomous vehicle in an autonomous mode, receiving one or more messages from a temperature sensor associated with an electrical device located on or in the autonomous vehicle while the autonomous vehicle is operated in the autonomous mode, determining a cooling technique to reduce the temperature of electrical device, and performing the cooling technique.

Temperature management system for autonomous vehicles

An autonomous vehicle includes a detection system for identifying the presence changes in wind incident on the autonomous vehicle, particularly wind gusts. The detection system may include one or more wind sensors, particularly those configured to detect wind incident on the vehicle from a direction that is transverse or perpendicular to the direction of motion of the autonomous vehicle. Additionally, systems may be present that correlate the detected wind gusts to changes in the behavior of the autonomous vehicle. The autonomous vehicle may react to the detected wind gusts by altering the vehicle's trajectory, by stopping the vehicle, or by communicating with a control center for further instructions.

Wind gust detection by an autonomous vehicle

Devices, systems, and methods for hardware-based time synchronization for heterogenous sensors are described. An example method includes generating a plurality of input trigger pulses having a nominal pulse-per-second (PPS) rate, generating, based on timing information derived from the plurality of input trigger pulses, a plurality of output trigger pulses, and transmitting the plurality of output trigger pulses to a sensor of a plurality of sensors, wherein a frequency of the plurality of output trigger pulses corresponds to a target operating frequency of the sensor, wherein, in a case that a navigation system coupled to the synchronization unit is functioning correctly, the plurality of input trigger pulses is generated based on a nominal PPS signal from the navigation unit, and wherein, in a case that the navigation system is not functioning correctly, the plurality of input trigger pulses is generated based on a simulated clock source of the synchronization unit.

Hardware-based time synchronization for heterogeneous sensors in autonomous vehicles

Disclosed are devices, systems and methods for the operational testing on autonomous vehicles. One exemplary method includes configuring a primary vehicular model with an algorithm, calculating one or more trajectories for each of one or more secondary vehicular models that exclude the algorithm, configuring the one or more secondary vehicular models with a corresponding trajectory of the one or more trajectories, generating an updated algorithm based on running a simulation of the primary vehicular model interacting with the one or more secondary vehicular models that conform to the corresponding trajectory in the simulation, and integrating the updated algorithm into an algorithmic unit of the autonomous vehicle.

Operational testing of autonomous vehicles

Image processing techniques are described to obtain an image from a camera located on a vehicle while the vehicle is being driven, cropping a portion of the obtained image corresponding to a region of interest, detecting an object in the cropped portion, adding a bounding box around the detected object, determining position(s) of reference point(s) on the bounding box, and determining a location of the detected object in a spatial region where the vehicle is being driven based on the determined one or more positions of the second set of one or more reference points on the bounding box.

Perception system for autonomous vehicles

Techniques are described for managing redundant steering system for a vehicle. A method includes sending a first control command that instructs a first motor coupled to a steering wheel in a steering system to steer a vehicle, receiving, after sending the first control command, a speed of the vehicle, a yaw rate of the vehicle, and a steering position of the steering wheel, determining, based at least on the speed and the yaw rate, an expected range of steering angles that describes values within which the first motor is expected to steer the vehicle based on the first control command, and upon determining that the steering position of a steering wheel is outside the expected range of steering angles, sending a second control command that instructs a second motor coupled to the steering wheel in the steering system to steer the vehicle.

Managing redundant steering system for autonomous vehicles

Devices, systems, and methods for a vehicular safety system in autonomous vehicles are described. An example method for safely controlling a vehicle includes selecting, based on a first control command from a first vehicle control unit, an operating mode of the vehicle, and transmitting, based on the selecting, the operating mode to an autonomous driving system, wherein the first control command is generated based on input from a first plurality of sensors, and wherein the operating mode corresponds to one of (a) a default operating mode, (b) a minimal risk condition mode of a first type that configures the vehicle to pull over to a nearest pre-designated safety location, (c) a minimal risk condition mode of a second type that configures the vehicle to immediately stop in a current lane, or (d) a minimal risk condition mode of a third type that configures the vehicle to come to a gentle stop.

Vehicle safety system for autonomous vehicles

Growing community of inventors

San Diego, CA, United States of America

Zehua Huang